DocumentCode :
229070
Title :
Visual analytics of large-scale climate model data
Author :
Pak Chung Wong ; Han-Wei Shen ; Leung, Ruby ; Hagos, Samson ; Teng-Yok Lee ; Xin Tong ; Kewei Lu
Author_Institution :
Pacific Northwest Nat. Lab., Richland, WA, USA
fYear :
2014
fDate :
9-10 Nov. 2014
Firstpage :
85
Lastpage :
92
Abstract :
This application paper presents a visual analytics tool designed to explore large-scale scientific data modeled after a natural climate phenomenon. The data are modeled on a high-performance computer and exported to a personal computer for interactive visualization. The system is co-designed by visual analytics researchers and domain scientists after a year of rapid prototyping and evaluation of multiple information and scientific visualization techniques using a model dataset that includes both scalar fields and flow fields. Five information-visualization and one scientific-visualization techniques are included in the visual analytics system to balance analytical effectiveness and computation time for large-scale interactive exploration. The paper discusses the system design, explains the design rationale, and shares computation performance and results of different visualization techniques. The primary contribution of this application paper is to show that we can interactively and effectively visualize a large amount of scientific model data on a modest desktop computer. The computation performance results of the individual visualization techniques and the overall system also provide benchmark references for other large-scale visualization development efforts.
Keywords :
climatology; data models; data visualisation; geophysics computing; interactive systems; parallel processing; analytical effectiveness; computation performance; design rationale; desktop computer; flow fields; high-performance computer; information-visualization; interactive visualization; large-scale climate model data; large-scale interactive exploration; large-scale scientific data; large-scale visualization development efforts; natural climate phenomenon; personal computer; rapid prototyping; scalar fields; scientific model data; scientific visualization techniques; system design; visual analytics system; visual analytics tool; Analytical models; Computational modeling; Data models; Data visualization; Meteorology; Three-dimensional displays; Visual analytics; Visual analytics application; climate analytics; large data analytics and visualization; scientific modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Large Data Analysis and Visualization (LDAV), 2014 IEEE 4th Symposium on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/LDAV.2014.7013208
Filename :
7013208
Link To Document :
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